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US 11,694,431 B2Granted
Systems and methods for skyline prediction for cyber-physical photovoltaic array control
AssigneeArizona Board of Regents on behalf of Arizona State University
InventorsSameeksha Katoch, Pavan Turaga, Andreas Spanias, Cihan Tepedelenlioglu
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Abstract
Various embodiments of a cyber-physical system for providing cloud prediction for photovoltaic array control are disclosed herein.
Claims9
A method for classifying a set of video features, comprising:
- accessing a video representative of a first set of video features;
- modeling the video representative of the first set of video features as a linear dynamical system;
- obtaining an observability matrix for the linear dynamical system;
- extracting a set of tangent vectors using the observability matrix, wherein the set of tangent vectors is representative of the linear dynamical system;
- developing a probability density function representative of the linear dynamical system based on the set of tangent vectors;
- assigning a score to a set of video features by evaluating the probability density function for each set of video features;
- obtaining a spatiotemporal representation of the set of video features in terms of Lyapunov exponents;
- and
- classifying a set of video features using a combination of the spatiotemporal representation and the score, wherein the largest Lyapunov exponents are representative of transition phases between a set of classes.
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A method for predicting a set of future video features, comprising:
- accessing a video, wherein the video is representative of a set of video features;
- developing a time series matrix using a set of pixel values from the video;
- developing a phase space matrix from the time series matrix, wherein the phase space matrix is representative of the time series matrix in phase space, wherein phase space models all possible states of a system;
- and
- calculating a set of trajectories in phase space, wherein the set of trajectories in phase space is calculated by performing kernel regression on a weighted average of neighboring points in phase space, wherein the neighboring points are selected using locality sensitive hashing;
- wherein the set of trajectories in phase space is representative of a predicted set of pixel values,
- wherein the predicted set of pixel values is representative of a set of future video features.
4 more elements
Dependencies are inferred from the claim text.